The otolith digital catalogue AFORO allows unknown otoliths to be classified automatically by using a comparison with its classified records. To do this, the otolith’s contour, which is extracted from an image, is used. In AFORO, otolith images follow a strict positional normalization. Only the left sagitta is considered, and the images must show the internal side of the whole otolith, with the sulcus acusticus visible, the dorsal side (D) placed in the dorsal position and the rostral side (R) placed on the right. The otolith in the incoming image to be classified must also follow the same positional normalization. Variations from the reference position worsen the classification results. In this article, robust contour descriptors are proposed to extend this functionality of AFORO to the images of otoliths that are poorly normalized, contain rotations, are entirely inverted or came from the right rather than the left sagitta. These descriptors are based on the discrete Fourier transform and could extend the classification functionality to incoming images that are taken and sent, for instance, from smartphones in a wide range of working conditions.